練習 3：特徵擷取和微調
在本練習中，您將使用特徵擷取和精細調整功能，運用 Google 的 Inception v3 模型，為練習 1 和 2 中的貓狗分類器，進一步提高準確度：
機器學習實務：圖片分類
除非另有註明，否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權，程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
上次更新時間：2025-01-28 (世界標準時間)。
[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["缺少我需要的資訊","missingTheInformationINeed","thumb-down"],["過於複雜/步驟過多","tooComplicatedTooManySteps","thumb-down"],["過時","outOfDate","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["示例/程式碼問題","samplesCodeIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-01-28 (世界標準時間)。"],[[["This exercise leverages Google's Inception v3 model through feature extraction and fine-tuning to enhance the accuracy of a cat-vs-dog image classifier."],["It builds upon the previous exercises on image classification, refining the model for better performance."],["You will practically implement these techniques using a provided Google Colab notebook."]]],[]]